10 Stochastic Simulation

from src.plot import plot_simulated_stoc_path_full2_singapore2


plot_simulated_stoc_path_full2_singapore2("RD_Plot", "","Percentage (%)", [0,8])

plot_simulated_stoc_path_full2_singapore("e", """""","Gigatonne", [6,20])

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
c:\Users\33678\ClimateSocialPolicy\sec10_stochastic_simulation_singapore.ipynb Cell 3 in <cell line: 1>()
----> <a href='vscode-notebook-cell:/c%3A/Users/33678/ClimateSocialPolicy/sec10_stochastic_simulation_singapore.ipynb#W2sZmlsZQ%3D%3D?line=0'>1</a> plot_simulated_stoc_path_full2_singapore("e", """""","Gigatonne", [6,20])

NameError: name 'plot_simulated_stoc_path_full2_singapore' is not defined

plot_simulated_stoc_path_full2_singapore("e", """Figure 9: Simulated Pathways of the Social Value of R&D  <br> Exponential of vertical axis gives economic value in units of consumption""","", [6,25])

plot_simulated_stoc_path_full2_singapore("LogSCGW_Plot", """Figure 9: Simulated Pathways of the Social Cost of Global Warming  <br> Exponential of vertical axis gives economic value in units of consumption""","", [6,14])

plot_simulated_stoc_path_full2_singapore("TA", """""","Celsius Degree(ᵒC)", [1,2.5])

plot_simulated_stoc_path_full2_singapore("distorted_tech_prob", "Figure 6: Distorted Probability of a Technology Change Jump","", [0,1])

plot_simulated_stoc_path_full2_singapore("distorted_damage_prob", "Figure 7: Distorted Probability of a Damage Jump","", [0,1])

import plotly.io as pio
import plotly.offline as pyo
import pandas as pd
import numpy as np
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import os
import sys
import pickle
import plotly.express as px

sys.path.append(os.path.dirname(os.getcwd()))
pyo.init_notebook_mode()
pio.templates.default = "none"

theta_list = pd.read_csv('data/model144.csv', header=None).to_numpy()[:, 0] / 1000.
gamma_3_list = np.linspace(0, 1./3, 20)
xi_list_fullaversion_low = [0.025, 0.050, 10000.]
xi_list_fullaversion_high = [0.075, 0.150, 10000.]
xi_list_uncertainty_low = [0.050]
xi_list_uncertainty_high = [0.150]

def plot_simulated_stoc_path_full2_singapore2(graph_type, graph_title, yaxis_label, graph_range):


    xi_base = 100000.
    psi_0 = 0.10583
    psi_1 = 0.5
    varrho = 1120.0
    delta = 0.01
    # fig = make_subplots(1, 2)
    color = ["#d62728", "darkgreen", "navy", "darkorange"]
    j_list = [16, 0, 2, 13, 14]

    fig = go.Figure()
    for abatement_cost in [0.1, 0.5]:
        for rho in [0.66, 1.0, 1.5]:

            if abatement_cost == 0.1:

                xi_list_fullaversion = [0.050]

            if abatement_cost == 0.5:

                xi_list_fullaversion = [0.150]

            folder = "./data_simul3/2jump_step_4.00,9.00_0.0,4.0_1.0,6.0_0.0,3.0_SS_0.2,0.1,0.1_LR_0.0025_FK_phi0_{}/".format(
                abatement_cost)
            i = 0

            for xi in xi_list_fullaversion:
                filename = "xi_a_{}_xi_k_{}_xi_c_{}_xi_j_{}_xi_d_{}_xi_g_{}_psi_0_{}_psi_1_{}_varrho_{}_rho_{}_delta_{}_" .format(
                    xi_base, xi, xi, xi, xi, xi, psi_0, psi_1, varrho, rho, delta)

                with open(folder + filename + "model_tech1_pre_damage_UD_simulstoccompile_40direct_direct", "rb") as f:
                    model_tech1_pre_damage = pickle.load(f)

                PathLength = 20
                Years = model_tech1_pre_damage["years"][:,0]

                Mat = model_tech1_pre_damage[graph_type][:, 0:PathLength]

                for j in range(5):

                    legend_name = "Path {}".format(j+1)
                    j_used = j_list[j]

                    fig.add_trace(go.Scatter(x=Years,
                                                y=Mat[:, j_used],
                                                name=legend_name,
                                                showlegend=True,
                                                visible=True,
                                                line=dict(width=8),
                                                #  visible=False
                                                ))

                fig.update_traces(visible=False, line=dict(width=8))

                i = i+1
    PathLength=5

    for i in range(PathLength):
        fig.data[3*PathLength + i]["visible"] = True
        # fig.data[3*2 + i+12]["visible"] = True

        fig.data[3*PathLength + i]["showlegend"] = True
        # fig.data[3*2 + 12]["showlegend"] = True

    buttons = []
    i = 0

    for abatement_cost in [0.1, 0.5]:
        for rho in [0.66, 1.0, 1.5]:

            if abatement_cost == 0.1:

                cost_label = "φ₀=0.1"
            if abatement_cost == 0.5:

                cost_label = "φ₀=0.5"

            # Hide all traces
            label = cost_label+r', ρ' + '= {:.2f}'.format(rho)

            button = dict(method='update',
                          args=[
                              {
                                  'visible': [False] * (2 * 3 * PathLength ),
                                  'showlegend': [False] * (2 * 3 * PathLength ),
                              },
                          ],
                          label=label)
            # Enable the two traces we want to see
            # print(button['args'][0]["visible"])

            for j in range(PathLength):

                button['args'][0]["visible"][PathLength*i + j] = True

                button['args'][0]["showlegend"][PathLength*i + j] = True

            i = i+1
            # Add step to step list
            buttons.append(button)



    fig.update_layout(
        updatemenus=[
            dict(
                type="dropdown",
                direction="down",
                buttons=buttons,
                active=3,
                x=0.6,
                y=1.05,
                pad={'r': 10, 't': 10})
        ],
    )

    fig.update_xaxes(showgrid=False, showline=True,
                    title="Years", range=[0, 40], linewidth=8)
    fig.update_yaxes(showgrid=False,
                    showline=True,
                    range=graph_range,
                     title_text=yaxis_label, linewidth=8
                    # tickformat=".2f"
                    )

    fig.update_layout(
        # title=graph_title,
        # barmode="overlay",
        plot_bgcolor="white",
        width=1100,
        height=700,
        font=dict(size=24),
        margin=dict(l=100, r=0,t=0))


    return fig

plot_simulated_stoc_path_full2_singapore2("RD_Plot", "","Percentage (%)", [0,8])

plot_simulated_stoc_path_full2_singapore2("e", """""","Gigatonne", [6,22])

plot_simulated_stoc_path_full2_singapore2("TA", """""","Celsius Degree(ᵒC)", [1,2.5])